{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Clean-Label Feature Collision Attacks on a Keras Classifier"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this notebook, we will learn how to use ART to run a clean-label feature collision poisoning attack on a neural network trained with Keras. We will be training our data on a subset of the CIFAR-10 dataset. The methods described are derived from [this paper](https://arxiv.org/abs/1804.00792) by Shafahi, Huang, et. al. 2018."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "import os, sys\n",
    "from os.path import abspath\n",
    "\n",
    "module_path = os.path.abspath(os.path.join('..'))\n",
    "if module_path not in sys.path:\n",
    "    sys.path.append(module_path)\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "from keras.models import load_model\n",
    "\n",
    "from art import config\n",
    "from art.utils import load_dataset, get_file\n",
    "from art.estimators.classification import KerasClassifier\n",
    "from art.attacks.poisoning import FeatureCollisionAttack\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "np.random.seed(301)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "(x_train, y_train), (x_test, y_test), min_, max_ = load_dataset('cifar10')\n",
    "\n",
    "num_samples_train = 1000\n",
    "num_samples_test = 1000\n",
    "x_train = x_train[0:num_samples_train]\n",
    "y_train = y_train[0:num_samples_train]\n",
    "x_test = x_test[0:num_samples_test]\n",
    "y_test = y_test[0:num_samples_test]\n",
    "\n",
    "class_descr = ['airplane', 'automobile', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load Model to be Attacked\n",
    "\n",
    "In this example, we using a RESNET50 model pretrained on the CIFAR dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "path = get_file('cifar_alexnet.h5',extract=False, path=config.ART_DATA_PATH,\n",
    "                url='https://www.dropbox.com/s/ta75pl4krya5djj/cifar_alexnet.h5?dl=1')\n",
    "classifier_model = load_model(path)\n",
    "classifier = KerasClassifier(clip_values=(min_, max_), model=classifier_model, use_logits=False, \n",
    "                             preprocessing=(0.5, 1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Choose Target Image from Test Set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "true_class: bird\n",
      "predicted_class: bird\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "target_class = \"bird\" # one of ['airplane', 'automobile', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']\n",
    "target_label = np.zeros(len(class_descr))\n",
    "target_label[class_descr.index(target_class)] = 1\n",
    "target_instance = np.expand_dims(x_test[np.argmax(y_test, axis=1) == class_descr.index(target_class)][3], axis=0)\n",
    "\n",
    "fig = plt.imshow(target_instance[0])\n",
    "\n",
    "print('true_class: ' + target_class)\n",
    "print('predicted_class: ' + class_descr[np.argmax(classifier.predict(target_instance), axis=1)[0]])\n",
    "\n",
    "feature_layer = classifier.layer_names[-2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Poison Training Images to Misclassify Test\n",
    "\n",
    "The attacker wants to make it such that whenever a prediction is made on this particular cat the output will be a horse."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "New test data to be poisoned (10 images):\n",
      "Correctly classified: 9\n",
      "Incorrectly classified: 1\n"
     ]
    }
   ],
   "source": [
    "base_class = \"frog\" # one of ['airplane', 'automobile', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']\n",
    "base_idxs = np.argmax(y_test, axis=1) == class_descr.index(base_class)\n",
    "base_instances = np.copy(x_test[base_idxs][:10])\n",
    "base_labels = y_test[base_idxs][:10]\n",
    "\n",
    "x_test_pred = np.argmax(classifier.predict(base_instances), axis=1)\n",
    "nb_correct_pred = np.sum(x_test_pred == np.argmax(base_labels, axis=1))\n",
    "\n",
    "print(\"New test data to be poisoned (10 images):\")\n",
    "print(\"Correctly classified: {}\".format(nb_correct_pred))\n",
    "print(\"Incorrectly classified: {}\".format(10-nb_correct_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "for i in range(0, 9):\n",
    "    pred_label, true_label = class_descr[x_test_pred[i]], class_descr[np.argmax(base_labels[i])]\n",
    "    plt.subplot(330 + 1 + i)\n",
    "    fig=plt.imshow(base_instances[i])\n",
    "    fig.axes.get_xaxis().set_visible(False)\n",
    "    fig.axes.get_yaxis().set_visible(False)\n",
    "    fig.axes.text(0.5, -0.1, pred_label + \" (\" + true_label + \")\", fontsize=12, transform=fig.axes.transAxes, \n",
    "                  horizontalalignment='center')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The captions on the images can be read: `predicted label (true label)`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Creating Poison Frogs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 10/10 [00:01<00:00,  9.76it/s]\n",
      "100%|██████████| 10/10 [00:00<00:00, 16.56it/s]\n",
      "100%|██████████| 10/10 [00:00<00:00, 15.97it/s]\n",
      "100%|██████████| 10/10 [00:00<00:00, 17.06it/s]\n",
      "100%|██████████| 10/10 [00:00<00:00, 16.40it/s]\n",
      "100%|██████████| 10/10 [00:00<00:00, 15.85it/s]\n",
      "100%|██████████| 10/10 [00:00<00:00, 17.06it/s]\n",
      "100%|██████████| 10/10 [00:00<00:00, 15.25it/s]\n",
      "100%|██████████| 10/10 [00:00<00:00, 15.91it/s]\n",
      "100%|██████████| 10/10 [00:00<00:00, 16.80it/s]\n"
     ]
    }
   ],
   "source": [
    "attack = FeatureCollisionAttack(classifier, target_instance, feature_layer, max_iter=10, similarity_coeff=256, watermark=0.3)\n",
    "poison, poison_labels = attack.poison(base_instances)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "poison_pred = np.argmax(classifier.predict(poison), axis=1)\n",
    "plt.figure(figsize=(10,10))\n",
    "for i in range(0, 9):\n",
    "    pred_label, true_label = class_descr[poison_pred[i]], class_descr[np.argmax(poison_labels[i])]\n",
    "    plt.subplot(330 + 1 + i)\n",
    "    fig=plt.imshow(poison[i])\n",
    "    fig.axes.get_xaxis().set_visible(False)\n",
    "    fig.axes.get_yaxis().set_visible(False)\n",
    "    fig.axes.text(0.5, -0.1, pred_label + \" (\" + true_label + \")\", fontsize=12, transform=fig.axes.transAxes, \n",
    "                  horizontalalignment='center')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice how the network classifies most of theses poison examples as frogs, and it's not incorrect to do so. The examples look mostly froggy. A slight watermark of the target instance is also added to push the poisons closer to the target class in feature space."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Training with Poison Images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1000, 32, 32, 3)\n",
      "(10, 32, 32, 3)\n",
      "Epoch 1/5\n",
      "252/252 [==============================] - 34s 136ms/step - loss: 0.4635 - acc: 0.92061s - loss: 0.4711 - a\n",
      "Epoch 2/5\n",
      "252/252 [==============================] - 26s 101ms/step - loss: 0.3405 - acc: 0.9325\n",
      "Epoch 3/5\n",
      "252/252 [==============================] - 26s 102ms/step - loss: 0.2121 - acc: 0.9534\n",
      "Epoch 4/5\n",
      "252/252 [==============================] - 26s 102ms/step - loss: 0.1950 - acc: 0.9742\n",
      "Epoch 5/5\n",
      "252/252 [==============================] - 30s 118ms/step - loss: 0.1888 - acc: 0.9712\n"
     ]
    }
   ],
   "source": [
    "classifier.set_learning_phase(True)\n",
    "print(x_train.shape)\n",
    "print(base_instances.shape)\n",
    "adv_train = np.vstack([x_train, poison])\n",
    "adv_labels = np.vstack([y_train, poison_labels])\n",
    "classifier.fit(adv_train, adv_labels, nb_epochs=5, batch_size=4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fooled Network Misclassifies Bird"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "true_class: bird\n",
      "predicted_class: frog\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.imshow(target_instance[0])\n",
    "\n",
    "print('true_class: ' + target_class)\n",
    "print('predicted_class: ' + class_descr[np.argmax(classifier.predict(target_instance), axis=1)[0]])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These attacks allow adversaries who can poison your dataset the ability to mislabel any particular target instance of their choosing without manipulating labels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
